Investigating the Impact of Blunt Force Trauma: A Probabilistic Study of Behind Armor Blunt Trauma Risk.
Behind armor blunt trauma
Military combat incapacitation scale
New injury severity score
Probabilistic finite element modeling
Response surface model
Journal
Annals of biomedical engineering
ISSN: 1573-9686
Titre abrégé: Ann Biomed Eng
Pays: United States
ID NLM: 0361512
Informations de publication
Date de publication:
26 Jun 2024
26 Jun 2024
Historique:
received:
02
02
2024
accepted:
13
06
2024
medline:
26
6
2024
pubmed:
26
6
2024
entrez:
26
6
2024
Statut:
aheadofprint
Résumé
Evaluating Behind Armor Blunt Trauma (BABT) is a critical step in preventing non-penetrating injuries in military personnel, which can result from the transfer of kinetic energy from projectiles impacting body armor. While the current NIJ Standard-0101.06 standard focuses on preventing excessive armor backface deformation, this standard does not account for the variability in impact location, thorax organ and tissue material properties, and injury thresholds in order to assess potential injury. To address this gap, Finite Element (FE) human body models (HBMs) have been employed to investigate variability in BABT impact conditions by recreating specific cases from survivor databases and generating injury risk curves. However, these deterministic analyses predominantly use models representing the 50th percentile male and do not investigate the uncertainty and variability inherent within the system, thus limiting the generalizability of investigating injury risk over a diverse military population. The DoD-funded I-PREDICT Future Naval Capability (FNC) introduces a probabilistic HBM, which considers uncertainty and variability in tissue material and failure properties, anthropometry, and external loading conditions. This study utilizes the I-PREDICT HBM for BABT simulations for three thoracic impact locations-liver, heart, and lower abdomen. A probabilistic analysis of tissue-level strains resulting from a BABT event is used to determine the probability of achieving a Military Combat Incapacitation Scale (MCIS) for organ-level injuries and the New Injury Severity Score (NISS) is employed for whole-body injury risk evaluations. Organ-level MCIS metrics show that impact at the heart can cause severe injuries to the heart and spleen, whereas impact to the liver can cause rib fractures and major lacerations in the liver. Impact at the lower abdomen can cause lacerations in the spleen. Simulation results indicate that, under current protection standards, the whole-body risk of injury varies between 6 and 98% based on impact location, with the impact at the heart being the most severe, followed by impact at the liver and the lower abdomen. These results suggest that the current body armor protection standards might result in severe injuries in specific locations, but no injuries in others.
Identifiants
pubmed: 38922366
doi: 10.1007/s10439-024-03564-3
pii: 10.1007/s10439-024-03564-3
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Office of Naval Research
ID : MTEC 18-04-I-PREDICT (W81XWH1590001)
Informations de copyright
© 2024. The Author(s) under exclusive licence to Biomedical Engineering Society.
Références
Cannon, L. Behind armour blunt trauma-an emerging problem. BMJ Military Health. 147:87–96, 2001.
Prather, R. N., C. L. Swann, and C.E. Hawkins. Backface Signatures of Soft Body Armors and the Associated Trauma Effects. US Department of Commerce, Technology Administration, National Technical Information Service, 1977.
Tam, W. The Development of a Physical Model of Non-penetrating Ballistic Injury Surgeon Lieutenant Commander L Cannon Royal Navy, 2001.
Mayorga, M., I. Anderson, J. van Bree, et al. Thoracic Response to Undefeated Body Armour. NATO Task Group TG-001, RTO, Report No RTO-TR-IST-999, 2010. https://booksgooglecoin/books/about/Thoracic_Response_to_Undefeated_Body_Arm.html.
Yoganandan, N., A. Shah, L. Somberg, et al. A novel paradigm to develop regional thoracoabdominal criteria for behind armor blunt trauma based on original data. Mil. Med. 188:598–605, 2023. https://doi.org/10.1093/milmed/usad272 .
doi: 10.1093/milmed/usad272
pubmed: 37948200
US Department of Justice. Ballistic Resistance of Body Armor NIJ Standard-0101.06. US Department of Justice.
Goldfarb, M. A., T. F. Ciurej, M. A. Weinstein, and L. Metker. A Method for Soft Body Armor Evaluation: Medical Assessment. Edgewood Arsenal Aberdeen Proving Ground, Report No EB-TR-74073, 1975.
Hanlon, E., and P. Gillich. Origin of the 44-mm behind-armor blunt trauma standard. Mil. Med. 177:333–339, 2012.
doi: 10.7205/MILMED-D-11-00303
pubmed: 22479923
Wilhelm, M. R. A Biomechanical Assessment of Female Body Armor. Detroit: Wayne State University, 2003.
Park, J. L., Y. S. Chi, M. H. Hahn, and T. J. Kang. Kinetic dissipation in ballistic tests of soft body armors. Exp. Mech. 52:1239–1250, 2012. https://doi.org/10.1007/s11340-011-9583-z .
doi: 10.1007/s11340-011-9583-z
Jennings, R. M., C. Malbon, F. Brock, et al. A preliminary study into injuries due to non-perforating ballistic impacts into soft body armour over the spine. Injury. 49:1251–1257, 2018. https://doi.org/10.1016/j.injury.2018.05.015 .
doi: 10.1016/j.injury.2018.05.015
pubmed: 29861310
Bass, C. R., R. S. Salzar, S. R. Lucas, et al. Injury risk in behind armor blunt thoracic trauma. Int. J. Occup. Saf. Ergon. 12:429–442, 2006.
doi: 10.1080/10803548.2006.11076702
pubmed: 17156618
Roberts, J. C., E. E. Ward, A. C. Merkle, and J. V. O’Connor. Assessing behind armor blunt trauma in accordance with the National Institute of Justice Standard for Personal Body Armor Protection using finite element modeling. J. Trauma Acute Care Surg. 62:1127–1133, 2007.
doi: 10.1097/01.ta.0000231779.99416.ee
Carr, D. J., I. Horsfall, and C. Malbon. Is behind armour blunt trauma a real threat to users of body armour? A systematic review. J. R. Army Med. Corps. 162:8–11, 2016. https://doi.org/10.1136/jramc-2013-000161 .
doi: 10.1136/jramc-2013-000161
pubmed: 24227791
Schmitt, K.-U., P. F. Niederer, M. H. Muser, and F. Walz. Methods in trauma biomechanics. In: Trauma Biomechanics: Accidental Injury in Traffic and Sports, edited by K.-U. Schmitt, P. F. Niederer, M. H. Muser, and F. Walz. Berlin: Springer, 2009, pp. 17–62.
Prat, N., F. Rongieras, J.-C. Sarron, et al. Contemporary body armor: technical data, injuries, and limits. Eur. J. Trauma Emerg. Surg. 38:95–105, 2012. https://doi.org/10.1007/s00068-012-0175-0 .
doi: 10.1007/s00068-012-0175-0
pubmed: 26815825
Bir, C., R. Lance, S. Stojsih-Sherman, and J. Cavanaugh. Behind armor blunt trauma: recreation of field cases for the assessment of backface signature testing. In: 30th International Symposium on Ballistics, 2017. https://doi.org/10.12783/ballistics2017/16912 .
Roberts, J. C., A. C. Merkle, P. J. Biermann, et al. Computational and experimental models of the human torso for non-penetrating ballistic impact. J. Biomech. 40:125–136, 2007. https://doi.org/10.1016/j.jbiomech.2005.11.003 .
doi: 10.1016/j.jbiomech.2005.11.003
pubmed: 16376354
Roberts, J. C., J. V. O’Connor, and E. E. Ward. Modeling the effect of non-penetrating ballistic impact as a means of detecting behind armor blunt trauma. J. Trauma. 58:1241–1251, 2005. https://doi.org/10.1097/01.ta.0000169805.81214.dc .
doi: 10.1097/01.ta.0000169805.81214.dc
pubmed: 15995477
Merkle, A. C., E. E. Ward, J. V. O’Connor, and J. C. Roberts. Assessing behind armor blunt trauma (BABT) under NIJ standard-0101.04 conditions using human torso models. J. Trauma. 64:1555–1561, 2008. https://doi.org/10.1097/TA.0b013e318160ff3a .
doi: 10.1097/TA.0b013e318160ff3a
pubmed: 18545123
Raftenberg, M. N. Modeling Thoracic Blunt Trauma; Towards a Finite-Element-Based Design Methodology for Body Armor. Army Research Lab Aberdeen Proving Ground MD.
Shen, W., Y. Niu, L. Bykanova, et al. Characterizing the interaction among bullet, body armor, and human and surrogate targets. J. Biomech. Eng. 2010. https://doi.org/10.1115/1.4002699 .
doi: 10.1115/1.4002699
pubmed: 21142315
Bracq, A., R. Delille, C. Maréchal, et al. Rib fractures prediction method for kinetic energy projectile impact: from blunt ballistic experiments on SEBS gel to impact modeling on a human torso FE model. Forensic Sci. Int. 297:177–183, 2019. https://doi.org/10.1016/j.forsciint.2019.02.007 .
doi: 10.1016/j.forsciint.2019.02.007
pubmed: 30802646
Chaufer, M., R. Delille, B. Bourel, et al. A new biomechanical FE model for blunt thoracic impact. Front. Bioeng. Biotechnol. 11:1152508, 2023. https://doi.org/10.3389/fbioe.2023.1152508 .
doi: 10.3389/fbioe.2023.1152508
pubmed: 37034254
pmcid: 10073536
Thompson, A. B., F. S. Gayzik, D. P. Moreno, et al. A paradigm for human body finite element model integration from a set of regional models. Biomed. Sci. Instrum. 48:423–430, 2012.
pubmed: 22846315
Iwamoto, M., Y. Nakahira, and H. Kimpara. Development and validation of the Total HUman Model for Safety (THUMS) toward further understanding of occupant injury mechanisms in precrash and during crash. Traffic Inj. Prev. 16:S36–S48, 2015. https://doi.org/10.1080/15389588.2015.1015000 .
doi: 10.1080/15389588.2015.1015000
pubmed: 26027974
Shigeta, K., Y. Kitagawa, and T. Yasuki. Development of next generation human FE model capable of organ injury prediction. In: Proceedings of the 21st Annual Enhanced Safety of Vehicles, 2009, pp. 15–18.
Schwartz, D., B. Guleyupoglu, B. Koya, et al. Development of a computationally efficient full human body finite element model. Traffic Inj. Prev. 16:S49–S56, 2015. https://doi.org/10.1080/15389588.2015.1021418 .
doi: 10.1080/15389588.2015.1021418
pubmed: 26027975
Gierczycka, D., B. Watson, and D. Cronin. Investigation of occupant arm position and door properties on thorax kinematics in side impact crash scenarios—comparison of ATD and human models. Int. J. Crashworthiness. 20:242–269, 2015. https://doi.org/10.1080/13588265.2014.998000 .
doi: 10.1080/13588265.2014.998000
Campbell, B. M., and D. S. Cronin. Coupled human body and side impact model to predict thoracic response. Int. J. Crashworthiness. 19:394–413, 2014. https://doi.org/10.1080/13588265.2014.909561 .
doi: 10.1080/13588265.2014.909561
Nicolella, D. P., B. H. Thacker, H. Katoozian, and D. T. Davy. Probabilistic risk analysis of a cemented hip implant. In: ASME-Publications-BED, 2001, vol 50, pp. 427–428.
Nicolella, D., W. Francis, A. Bonivtch, et al. Development, verification, and validation of a parametric cervical spine injury prediction model. In: 47th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference; 14th AIAA/ASME/AHS Adaptive Structures Conference; 7th American Institute of Aeronautics and Astronautics, Newport, Rhode Island, 2006.
Thacker, B. H., D. P. Nicolella, S. Kumaresan, et al. Probabilistic injury analysis of the human cervical spine. In: ASME-Publications-BED, 2001, vol 50, pp. 879–880.
Nicolella, D. P., B. H. Thacker, H. Katoozian, and D. T. Davy. The effect of three-dimensional shape optimization on the probabilistic response of a cemented femoral hip prosthesis. J. Biomech. 39:1265–1278, 2006.
doi: 10.1016/j.jbiomech.2005.03.010
pubmed: 15961093
Iraeus, J., K. Brolin, and B. Pipkorn. Generic finite element models of human ribs, developed and validated for stiffness and strain prediction—to be used in rib fracture risk evaluation for the human population in vehicle crashes. J. Mech. Behav. Biomed. Mater.106:103742, 2020. https://doi.org/10.1016/j.jmbbm.2020.103742 .
doi: 10.1016/j.jmbbm.2020.103742
pubmed: 32250953
Rampersadh, C., A. M. Agnew, S. Malcolm, et al. Factors affecting the numerical response and fracture location of the GHBMC M50 rib in dynamic anterior–posterior loading. J. Mech. Behav. Biomed. Mater.136:105527, 2022.
doi: 10.1016/j.jmbbm.2022.105527
pubmed: 36306670
Schoell, S. L., A. A. Weaver, N. A. Vavalle, and J. D. Stitzel. Age- and sex-specific thorax finite element model development and simulation. Traffic Inj. Prev. 16:S57–S65, 2015.
doi: 10.1080/15389588.2015.1005208
pubmed: 26027976
Cronin, D., M. Bustamante, J. Barker, et al. Assessment of thorax finite element model response for behind armor blunt trauma impact loading using an epidemiological database. J. Biomech. Eng.143:031007, 2021.
doi: 10.1115/1.4048644
pubmed: 33009546
Bustamante, M., and D. Cronin. Impact location dependence of behind armor blunt trauma injury assessed using a human body finite element model. J. Biomech. Eng. 146(3):1–24, 2023.
Frazer, L., V. Kote, Z. Hostetler, et al. A comparative analysis of dimensionality reduction surrogate modeling techniques for full human body finite element impact simulations. Comput. Methods Biomech. Biomed. Eng. 2023. https://doi.org/10.1080/10255842.2023.2236747 .
doi: 10.1080/10255842.2023.2236747
Lawnick, M. M., H. R. Champion, T. Gennarelli, et al. Combat injury coding: a review and reconfiguration. J. Trauma Acute Care Surg. 75:573, 2013. https://doi.org/10.1097/TA.0b013e3182a53bc6 .
doi: 10.1097/TA.0b013e3182a53bc6
pubmed: 24064868
Osler, T., S. P. Baker, and W. Long. A modification of the injury severity score that both improves accuracy and simplifies scoring. J. Trauma 43:922–925; discussion 925–926, 1997. https://doi.org/10.1097/00005373-199712000-00009 .
Op‘t Eynde, J., C. P. Eckersley, R.S. Salzar, and B. D. Stemper. Behind armour blunt trauma (BABT) indenter simulating high-velocity impacts from rifle rounds on hard body armour. In: Personal Armour Systems Symposium, Copenhagen, Denmark, 2020.
Hostetler, Z. Development of a 50th percentile male warfighter model for incapacitation prediction in behind armor blunt trauma. In: Military Health System Research Symposium, 2023.
Eliason, T., J. Coogan, and D. Nicolella. Hierarchical verification and validation of human body computational models. In: IRCOBI Conference Proceedings, 2016.
Zeng, W., S. Mukherjee, A. Caudillo, et al. Evaluation and validation of thorax model responses: a hierarchical approach to achieve high biofidelity for thoracic musculoskeletal system. Front. Bioeng. Biotechnol. 2021. https://doi.org/10.3389/fbioe.2021.712656 .
doi: 10.3389/fbioe.2021.712656
pubmed: 35087802
pmcid: 8741272
Thacker, B. H., W. L. Francis, and D. P. Nicolella. Model validation and uncertainty quantification applied to cervical spine injury assessment. In: Computational Uncertainty in Military Vehicle Design 26-1. NATO, 2007.
Avants, B. B., N. J. Tustison, G. Song, et al. A reproducible evaluation of ANTs similarity metric performance in brain image registration. Neuroimage. 54:2033–2044, 2011. https://doi.org/10.1016/j.neuroimage.2010.09.025 .
doi: 10.1016/j.neuroimage.2010.09.025
pubmed: 20851191
McFarland, J. M., J. A. Dimeo, and B. J. Bichon. Gaussian process response surface modeling and global sensitivity analysis using NESSUS. In: International Conference on Uncertainty Quantification in Computational Sciences and Engineering, UNCECOMP 2017, 2nd ECCOMAS Thematic Conference, 2017.
Norton, N., S. Crimmons, Z. Hostetler, et al. The I-PREDICT 50th percentile male warfighter finite element model: development and validation of the head and neck. Ann. Biomed. Eng.
DiSerafino, D., D. Jones, Z. Hostetler, et al. The I-PREDICT 50th percentile male warfighter finite element model: development and validation of the thoracolumbar spine. Ann. Biomed. Eng. 2024. https://doi.org/10.1007/s10439-024-03522-z .
doi: 10.1007/s10439-024-03522-z
pubmed: 38780890
Hostetler, Z., D. DiSerafino, A. Kalmar-Gonzalo, et al. The I-PREDICT 50th percentile male warfighter finite element model: development and validation of the torso for incapacitation prediction in behind armor blunt trauma.
Kroell, C. K., D. C. Schneider, and A. M. Nahum. Impact tolerance and response of the human thorax II. SAE Trans. 83:3724–3762, 1974.
Villani, C. The Wasserstein distances. In: Optimal Transport: Old and New, edited by C. Villani. Berlin: Springer, 2009, pp. 93–111.
doi: 10.1007/978-3-540-71050-9_6
Seifert, J., J. Koser, A. Shah, et al. Impactor displacement as a predictor of thoraco-abdominal organ injury: comparison of isolated organ to whole body tests (in review). Ann. Biomed. Eng.
Forman, J. L., R. W. Kent, K. Mroz, et al. Predicting rib fracture risk with whole-body finite element models: development and preliminary evaluation of a probabilistic analytical framework. Ann. Adv. Automot. Med. 56:109–124, 2012.
pubmed: 23169122
pmcid: 3503420
Moore, E. E., T. H. Cogbill, M. A. Malangoni, et al. Organ injury scaling. Surg. Clin. N. Am. 75:293–303, 1995. https://doi.org/10.1016/s0039-6109(16)46589-8 .
doi: 10.1016/s0039-6109(16)46589-8
pubmed: 7899999
Kozar, R. A., M. Crandall, K. Shanmuganathan, et al. Organ injury scaling 2018 update: spleen, liver, and kidney. J. Trauma Acute Care Surg. 85:1119–1122, 2018. https://doi.org/10.1097/TA.0000000000002058 .
doi: 10.1097/TA.0000000000002058
pubmed: 30462622
Gennarelli, T. A., and E. Wodzin. AIS 2005: a contemporary injury scale. Injury. 37:1083–1091, 2006. https://doi.org/10.1016/j.injury.2006.07.009 .
doi: 10.1016/j.injury.2006.07.009
pubmed: 17092503
Wagner, R. B., W. O. Crawford, and P. P. Schimpf. Classification of parenchymal injuries of the lung. Radiology. 167:77–82, 1988. https://doi.org/10.1148/radiology.167.1.3347751 .
doi: 10.1148/radiology.167.1.3347751
pubmed: 3347751
Melvin, J. W., A. M. Nahum, and N. Yoganandan. Accidental Injury: Biomechanics and Prevention. New York: Springer, 2015.
Li, Z., M. W. Kindig, J. R. Kerrigan, et al. Rib fractures under anterior–posterior dynamic loads: experimental and finite-element study. J. Biomech. 43:228–234, 2010. https://doi.org/10.1016/j.jbiomech.2009.08.040 .
doi: 10.1016/j.jbiomech.2009.08.040
pubmed: 19875122
Holcombe, S. A., Y.-S. Kang, B. A. Derstine, et al. Regional maps of rib cortical bone thickness and cross-sectional geometry. J. Anat. 235:883–891, 2019. https://doi.org/10.1111/joa.13045 .
doi: 10.1111/joa.13045
pubmed: 31225915
pmcid: 6794212
Zhao, J., and G. Narwani. Development of a human body finite element model for restraint system R&D applications. In: The 19th International Technical Conference on the Enhanced Safety of Vehicles (ESV), Paper, 2005. Citeseer, 2005.
Gaur, P., A. Chawla, K. Verma, et al. Characterisation of human diaphragm at high strain rate loading. J. Mech. Behav. Biomed. Mater. 60:603–616, 2016. https://doi.org/10.1016/j.jmbbm.2016.02.031 .
doi: 10.1016/j.jmbbm.2016.02.031
pubmed: 27062242
Comley, K., and N. Fleck. The compressive response of porcine adipose tissue from low to high strain rate. Int. J. Impact Eng. 46:1–10, 2012. https://doi.org/10.1016/j.ijimpeng.2011.12.009 .
doi: 10.1016/j.ijimpeng.2011.12.009
Hampton, C. E., and M. Kleinberger. Material Models for the Human Torso Finite Element Model. US Army Research Laboratory (ARL), Aberdeen Proving Ground, MD, 2018.
Zhai, X., and W. W. Chen. Compressive mechanical response of porcine muscle at intermediate (100/s–102/s) strain rates. Exp. Mech. 59:1299–1305, 2019. https://doi.org/10.1007/s11340-018-00456-1 .
doi: 10.1007/s11340-018-00456-1
Song, B., W. Chen, Y. Ge, and T. Weerasooriya. Dynamic and quasi-static compressive response of porcine muscle. J. Biomech. 40:2999–3005, 2007. https://doi.org/10.1016/j.jbiomech.2007.02.001 .
doi: 10.1016/j.jbiomech.2007.02.001
pubmed: 17448479
Shergold, O. A., N. A. Fleck, and D. Radford. The uniaxial stress versus strain response of pig skin and silicone rubber at low and high strain rates. Int. J. Impact Eng. 32:1384–1402, 2006. https://doi.org/10.1016/j.ijimpeng.2004.11.010 .
doi: 10.1016/j.ijimpeng.2004.11.010
Kemper, A. R., C. McNally, E. A. Kennedy, et al. Material properties of human rib cortical bone from dynamic tension coupon testing. Stapp Car Crash J. 49:199–230, 2005. https://doi.org/10.4271/2005-22-0010 .
doi: 10.4271/2005-22-0010
pubmed: 17096275
Katzenberger, M. J., D. L. Albert, A. M. Agnew, and A. R. Kemper. Effects of sex, age, and two loading rates on the tensile material properties of human rib cortical bone. J. Mech. Behav. Biomed. Mater.102:103410, 2020. https://doi.org/10.1016/j.jmbbm.2019.103410 .
doi: 10.1016/j.jmbbm.2019.103410
pubmed: 31655338
Gayzik, F. S., J. J. Hoth, M. Daly, et al. A finite element-based injury metric for pulmonary contusion: investigation of candidate metrics through correlation with computed tomography. Stapp Car Crash J. 51:189–209, 2007. https://doi.org/10.4271/2007-22-0009 .
doi: 10.4271/2007-22-0009
pubmed: 18278598
Kemper, A. R., A. C. Santago, J. D. Stitzel, et al. Biomechanical response of human spleen in tensile loading. J. Biomech. 45:348–355, 2012. https://doi.org/10.1016/j.jbiomech.2011.10.022 .
doi: 10.1016/j.jbiomech.2011.10.022
pubmed: 22078273
Snedeker, J. G., M. Barbezat, P. Niederer, et al. Strain energy density as a rupture criterion for the kidney: impact tests on porcine organs, finite element simulation, and a baseline comparison between human and porcine tissues. J. Biomech. 38:993–1001, 2005. https://doi.org/10.1016/j.jbiomech.2004.05.030 .
doi: 10.1016/j.jbiomech.2004.05.030
pubmed: 15797581
Yamada, H. Strength of Biological Materials. Philadelphia: Williams & Wilkins, 1970.
Kemper, A. R., A. C. Santago, J. D. Stitzel, et al. Biomechanical response of human liver in tensile loading. Ann. Adv. Automot. Med. 54:15–26, 2010.
pubmed: 21050588
pmcid: 3242546
Javali, R. H., A. Patil, and M. Srinivasarangan. Comparison of injury severity score, new injury severity score, revised trauma score and trauma and injury severity score for mortality prediction in elderly trauma patients. Indian J. Crit. Care Med. Peer Rev. Off. Publ. Indian Soc. Crit. Care Med. 23:73, 2019.
Tommasini, S. M., P. Nasser, M. B. Schaffler, and K. J. Jepsen. Relationship between bone morphology and bone quality in male tibias: implications for stress fracture risk. J. Bone Miner. Res. 20:1372–1380, 2005. https://doi.org/10.1359/JBMR.050326 .
doi: 10.1359/JBMR.050326
pubmed: 16007335
Murach, M. M., Y.-S. Kang, S. D. Goldman, et al. Rib geometry explains variation in dynamic structural response: potential implications for frontal impact fracture risk. Ann. Biomed. Eng. 45:2159–2173, 2017. https://doi.org/10.1007/s10439-017-1850-4 .
doi: 10.1007/s10439-017-1850-4
pubmed: 28547660
pmcid: 5860670
Bredbenner, T. L., R. L. Mason, L. M. Havill, et al. Fracture risk predictions based on statistical shape and density modeling of the proximal femur. J. Bone Miner. Res. 29:2090–2100, 2014. https://doi.org/10.1002/jbmr.2241 .
doi: 10.1002/jbmr.2241
pubmed: 24692132
Miller, P. R., M. A. Croce, T. K. Bee, et al. ARDS after pulmonary contusion: accurate measurement of contusion volume identifies high-risk patients. J. Trauma Acute Care Surg. 51:223, 2001.
doi: 10.1097/00005373-200108000-00003